Result for 1EDDDB49FD3FD6E01D963CB683CD5F5851E79DF7

Query result

Key Value
FileName./usr/lib64/R/library/LearnBayes/R/LearnBayes.rdb
FileSize102236
MD51DEA71D9382C016D761BD0484293EDD9
SHA-11EDDDB49FD3FD6E01D963CB683CD5F5851E79DF7
SHA-256D1F732386A5264AC7F5BA652FC57B1C7A1870FC3F1183D2510691A486FEC7B7D
SSDEEP1536:zqre3XsMF+YVVIjLV6s6fJFJ5tSssiw/iOmNqD1qTjtG4XM2+IJp6WRHlKMS6+qM:d+YVVmLMrvtF6yo1Wjk4fRLXllQq56
TLSHT12CA3121880A07E2094CB640DF353AFF3D358B15E4FD69E7175A4E192B9DB828B61263F
hashlookup:parent-total1
hashlookup:trust55

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Parents (Total: 1)

The searched file hash is included in 1 parent files which include package known and seen by metalookup. A sample is included below:

Key Value
MD5B685B913CD2C18A916FB45308DCC68A5
PackageArchx86_64
PackageDescriptionA collection of functions helpful in learning the basic tenets of Bayesian statistical inference. It contains functions for summarizing basic one and two parameter posterior distributions and predictive distributions. It contains MCMC algorithms for summarizing posterior distributions defined by the user. It also contains functions for regression models, hierarchical models, Bayesian tests, and illustrations of Gibbs sampling.
PackageNameR-LearnBayes
PackageRelease1.31
PackageVersion2.15.1
SHA-1668F26064F3AF757874499A0B4BA51E5B39E1224
SHA-2561A58DF996E307D77188BAE983899A6D320D6AA1CC3B3A50F63E80200F359EAE3